For years, b2b and b2c marketers have relied on attitudinal segmentation research to help them group their current customer base, and potential customers as well, for communication, promotion, marketing and experience initiatives. The thesis has been that, by asking a small, but meaningful, set of attitudinal questions, they would be able to develop an index, algorithm, or framework equation that ranked these consumers by propensity to buy, both near-term and long-term. Similar thinking has been applied by some organizations, as they conduct employee satisfaction and engagement research.
These frameworks – they’re arithmetic, so we can’t rightly call them ‘models – typically include questions regarding the importance of elements like value for money, acting with the consumer’s interests in mind, credit and payment terms, having knowledgeable employees, offering products which will meet the consumer’s needs, and the like. From these questions, basic segment categorization can be determined; and, once these three, four, or five segments are established, we’ve often seen companies go on to build assumptive marketing, experience, or communication plans, and conduct further, more detailed and targeted, research around them.
The goal of these approaches is to produce attitudinal segments which the questions can predict with high accuracy, often in the 80% or 90% range. This creates what economists would call a “post hoc ergo propter hoc” situation, Latin for “after this, therefore because of this.” It is a classical logic fallacy, essentially saying that A occurred (the responses to the attitudinal questions), and then B occurred (the cuts, or segments, of consumers or employees). Thus, the fallacy concludes, A caused B. So, for our example, once the B, or segment creation, stage has been established, further fallacies, such as creating reliable marketing, operational, and experiential strategies around these supposed propensities, can be built. It’s a classic situation, where correlation is thought to be the same as causation. As your economics or stat professors should have told you (and repeated, for emphasis), correlation and causation are far from being identical concepts.
As a consultant and analyst, I’ve too often seen the unfortunate result of the application of this research and analytics approach play out on a first hand basis – - coming in after the customer or employee segmentation study had been fielded, compiled and presented to interpret, and apply, the findings. Here’s a recent one, reflective of the array of negative outcomes which can occur. A client in the retail office products market had been using an attitudinally-derived element importance question framework for small business market segmentation purposes. The attitudinal segment assumptions went unquestioned among executives until follow-up qualitative research was conducted to better shape and target their planned marketing and operational initiatives. Importance of certain products and reliable service were identified in the segmentation research as key areas of focus and opportunity for the office products retailer; but, in the qualitative research following the quantitative segmentation study, power of both focus areas appeared, anecdotally, to be consistent across ALL segments, not just those where there was attitudinal strength. And, even though implied supplier roles were suggested to build purchases, this was much more ‘leap of faith’ based on the established quantitative research segment personas than actual qualitative research findings.
There are related issues with what we can describe as quasi-behavioral measures, such as single question metrics (likelihood to recommend to a friend or colleague or the amount of service effort required on the part of a consumer), or traditional customer loyalty indices (where future purchase intent is included, but also attitudinal questions such as overall satisfaction). It’s not that they don’t offer some segmentation guidance. They do – on a macro or global level; but they tend to be less effective on a granular level, especially where elements of customer touchpoint experience are involved: (http://www.customerthink.com/blog/customer_effort_score_and_nps_gangnam_style_metrics and http://www.customerthink.com/blog/sorry_nps_i_m_not_buying_it)
And, they tend to have limitations as predictors of segment behavior, a key business outcome for marketers and operations management. When compared to research and analysis techniques such as customer advocacy and customer brand-bonding, which are contemporary, real-world frameworks built on actual customer experience -(http://www.customerthink.com/article/customer_advocacy_behavior_personal_brand_connection) – high satisfaction scores, high index scores, and high net recommendation scores produced likely future purchase results (in studies across multiple industries) which were often 50% to 75% lower than advocacy or brand bonding frameworks. I’d be happy to provide proof for anyone interested in reviewing the findings.
So, that’s the scenario. The challenge, and potential danger, for marketers and those responsible for optimizing customer experience (and HR for employees) is that these attitudinal and quasi-behavioral questions are just that – attitudes and quasi-behaviors. Attitudes are fairly superficial, reactive feelings, and tend to be both tactical and reactive. And, because they are so transitory, their predictive value is often unstable and unreliable. Quasi-behaviors are also open to many similar challenges. More importantly, attitudes and quasi-behaviors are not behaviors, such as high probability downstream purchase intent based on actual previous purchase, evidence of positive and negative word-of-mouth about a brand based on prior personal experience, and brand favorability level based on experience. These are especially valuable in understanding competitive set, and they have real, and very stable, predictive and analytical value for marketers.
For the lessons, I’ve often used the works of Charles Dickens as a reference point. As Jaggers, the lawyer, said to Pip in Dickens’, Great Expectations,” take nothing on its looks; take everything on evidence. There’s no better rule.” For marketers (or HR executives), that’s excellent shorthand for taking everything about consumers on behavior, and perceptions based on documented personal experience, rather than attitudes and quasi-behaviors.